Computation of the chi square and Poisson distribution
SIAM Journal on Scientific and Statistical Computing
Computing Poisson probabilities
Communications of the ACM
Numerical transient analysis of Markov models
Computers and Operations Research
The UltraSAN modeling environment
Performance Evaluation - Special issue: performance modeling tools
A computationally efficient technique for transient analysis of repairable Markovian systems
Performance Evaluation
Numerical Computation of Sojourn-Time Distributions in Queuing Networks
Journal of the ACM (JACM)
Availability Analysis of Repairable Computer Systems and Stationarity Detection
IEEE Transactions on Computers
IEEE Transactions on Computers
SPNP: Stochastic Petri Net Package
PNPM '89 The Proceedings of the Third International Workshop on Petri Nets and Performance Models
Computers and Operations Research
A New General-Purpose Method for the Computation of the Interval Availability Distribution
INFORMS Journal on Computing
Hi-index | 14.98 |
Rewarded homogeneous continuous-time Markov chain (CTMC) models can be used to analyze performance, dependability and performability attributes of computer and telecommunication systems. In this paper, we consider rewarded CTMC models with a reward structure including reward rates associated with states and two measures summarizing the behavior in time of the resulting reward rate random variable: the expected transient reward rate at time t and the expected averaged reward rate in the time interval [0,t]. Computation of those measures can be performed using the randomization method, which is numerically stable and has good error control. However, for large stiff models, the method is very expensive. Exploiting the existence of a quasistationary distribution in the subset of transient states of discrete-time Markov chains with a certain structure, we develop a new variant of the (standard) randomization method, randomization with quasistationarity detection, covering finite CTMC models with state space S\cup\{f_1,f_2,\ldots,f_A\}, A\geq 1, where all states in S are transient and reachable among them and the states f_i are absorbing. The method has the same good properties as the standard randomization method and can be much more efficient. We also compare the performance of the method with that of regenerative randomization.